Identifying Necessary Components for Open Ended Evolution
Anya Vostinar, Emily Dolson, Michael Wiser, and Charles Ofria
June 3rd, 2016
Open-Ended Evolution is a huge concept
- To make scientific progress, we need a way to approach it incrementally
- Metrics of relative open-endedness allow this
- Complexity barriers
Our approach
- Last year we presented a suite of four metrics:
- Change
- Novelty
- Ecology
- Complexity
- Here, we test these metrics in a simple, well-studied system: NK landscapes

NK Landscapes
- Popular model for studying evolutionary dynamics in bitstrings
- N = length of bitstring
- K = Epistasis
1 0 1 1 1 0 0
Filtering out noise
- Evolution is an inherently noisy process
- Not all parts of a genome contribute to its success
- Many members of a population are the result of deleterious mutations
Filtering the genome
- Determine the fitness effect of changing each site in genome
- If negative, that site is informative - keep it
- Ignore all other sites
Example goes here
Filtering the population
- Previous approaches:
- Evolutionary activity statistics shadow run
- Fossil record
- We build on Bedau et. al.’s approach to the fossil record

Change
- Do the strategies in the population keep changing?
- In may EC systems, they don’t
Novelty
- Do new strategies keep appearing?
Ecology
- Does the diversity of strategies in the population keep increasing?
Complexity
- Does the maximum complexity in the population keep increasing?
Changing environments example
Change

Change

Novelty

Novelty

Ecology

Ecology

Complexity

Complexity

Conclusions
- Metrics intuitively reflect evolutionary dynamics
- By measuring the effects of different treaments, we can zero in on which conditions are necessary for open-ended evolution
Acknowledgements
Co-authors:

Funding sources:
